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program has been designed so that it will never attempt to read and then reread a row of the database during a single transaction. In this case, the inconsistent data problem can t occur because of the program structure. Alternatively, maybe the application designer knows that all of a program s access to particular tables of a database is read-only. If the programmer can convey information like this to the DBMS, some of the overhead of SQL transactions can be eliminated. The SQL1 standard did not address this database performance issue, and most of the major DBMS brands implemented proprietary schemes for enhancing the performance of SQL transactions. The SQL2 standard specified a new SET TRANSACTION statement whose function is to specify the level of SQL transaction-model support that an application needs. You don t need to use the SET TRANSACTION statement for casual use of SQL or for relatively simple or low-volume SQL transaction processing. To fully understand its operation, it s useful to understand the locking and other techniques used by commercial DBMS products to implement multiuser SQL transactions. The remainder of this chapter discusses locking, the performance-optimizing capabilities of SQL2, and the various DBMS brands that depend on it.
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Most major DBMS products use sophisticated locking techniques to handle concurrent SQL transactions for many simultaneous users. However, the basic concepts behind locking and transactions are very simple. Figure 12-10 shows a simple locking scheme and how it handles contention between two concurrent transactions. As Transaction A in the figure accesses the database, the DBMS automatically locks each piece of the database that the transaction retrieves or modifies. Transaction B proceeds in parallel, and the DBMS also locks the pieces of the database that it accesses. If Transaction B tries to access part of the database that has been locked by Transaction A, the DBMS blocks Transaction B, causing it to wait for the data to be unlocked. The DBMS releases the locks held by Transaction A only when it ends in a COMMIT or ROLLBACK operation. The DBMS then unblocks Transaction B, allowing it to proceed. Transaction B can now lock that piece of the database on its own behalf, protecting it from the effects of other transactions. As the figure shows, the locking technique temporarily gives a transaction exclusive access to a piece of a database, preventing other transactions from modifying the locked data. Locking thus solves all of the concurrent transaction problems. It prevents lost updates, uncommitted data, and inconsistent data from corrupting the database. However, locking introduces a new problem it may cause a transaction to wait for a very long time while the pieces of the database that it wants to access are locked by other transactions.
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Locking can be implemented at various levels of the database. In its most basic form, the DBMS could lock the entire database for each transaction. This locking strategy
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Figure 12-10.
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would be simple to implement, but it would allow processing of only one transaction at a time. If the transaction included any think time at all (such as time to discuss an order with a customer), all other access to the database would be blocked during that time, leading to unacceptably slow performance. However, database-level locking may be appropriate for certain types of transactions, such as those that modify the structure of the database or for complex queries that must sequentially scan many large tables. In these cases, it may be more efficient to rapidly do a single locking operation, quickly
12:
Transaction Processing
execute the database operation, and then quickly unlock the database than to individually lock dozens of tables. An enhanced form of locking is table-level locking. In this scheme, the DBMS locks only the tables accessed by a transaction. Other transactions can concurrently access other tables. This technique permits more parallel processing, but can still lead to unacceptably slow performance in applications such as order entry, where many users must share access to the same table or tables. Many DBMS products implement locking at the page level. In this scheme, the DBMS locks individual blocks of data (pages) from the disk as they are accessed by a transaction. Other transactions are prevented from accessing the locked pages but may access (and lock for themselves) other pages of data. Page sizes of 2KB, 4KB, and 16KB are commonly used. Since a large table will be spread out over hundreds or thousands of pages, two transactions trying to access two different rows of a table will usually be accessing two different pages, allowing the two transactions to proceed in parallel. Over the last several years, most of the major commercial DBMS systems have moved beyond page-level locking to row-level locks. Row-level locking allows two concurrent transactions that access two different rows of a table to proceed in parallel, even if the two rows fall in the same disk block. While this may seem a remote possibility, it can be a real problem with small tables containing small records, such as the OFFICES table in the sample database. Row-level locking provides a high degree of parallel transaction execution. Unfortunately, keeping track of locks on variable-length pieces of the database (in other words, rows) rather than fixed-size pages is a much more complex task, so increased parallelism comes at the cost of more sophisticated locking logic and increased overhead. In fact, for certain transactions or applications, the overhead of row-level locking might be greater than the performance gains of permitting more parallel operation within the database. Some DBMS products address this situation by automatically promoting many individual row-level locks into a page-level or table-level lock when the number of row-level locks for a given transaction rises above a certain limit. As this example shows, it s not always the case that a more granular (smaller) level of lock implementation is better; the best scheme heavily depends on the specific transactions and the SQL operations that they contain. It s theoretically possible to move beyond row-level locking to locking at the individual data item level. In theory, this would provide even more parallelism than row-level locks, because it would allow concurrent access to the same row by two different transactions, provided they were accessing different sets of columns. The overhead in managing item-level locking, however, has thus far outweighed its potential advantages. No commercial SQL DBMS uses item-level locking. In fact, locking is an area of considerable research in database technology, and the locking schemes used in commercial DBMS products are much more sophisticated than the fundamental scheme described here. The most straightforward of these advanced locking schemes, using shared and exclusive locks, is described in the next section.
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